Artificial intelligence (AI) is revolutionizing the world with its endless applications. The platforms built on AI are omnipresent, accelerating the pace of developing life-saving drugs and reducing operations costs. The building block of AI technologies is the neural networks, called artificial neural networks (ANN), that stimulate the human brain's analyzing and processing abilities to solve complex problems. The unique characteristics of ANN (such as efficient data handling, low complexity, reduced computation and storage requirements) have huge potential for a wide range of disciplines, including medical sciences [1]} (especially in the areas of cardiology [2]}, radiology [3]}, oncology [4]}, urology [5]}), veterinary [6]}, stock exchange [7]}, law enforcement department [8]}, ecology [9]}, human resource management [10]}, and cybersecurity [11]}. The ANN are mainly based on mathematical models inspired by biological nervous systems such as brain routes information. The ANN works similarly to an adaptive system, which updates its configuration in the learning phase and can be modeled for a specific application, such as data classification and pattern categorization. A neural network consists of three basic layers (i.e., input layer, hidden layer, and output layer). Based on these layers, ANN can be categorized into single-layer Feed-Forward Neural Network (FFNN) [12]}, multilayer feed-forward network [13]}, a single node with its feedback, and a multilayer recurrent network [14]}.
